The conditional maximum likelihood estimation for the Cox-Aalen model with doubly truncated data

• Published in: Statistics (Berlin, DDR) Vol. 59; no. 1; pp. 228 - 245
• Main Authors: Su, Chun-Lung, Shen, Pao-sheng
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.01.2025; Taylor & Francis Ltd
• Subjects: additive hazard regression; Algorithms; conditional likelihood; Cox model; double truncation; EM algorithm; Maximum likelihood estimation; Maximum likelihood estimators; Parameter estimation; Primary: 62N99; Regression models; Secondary: 62N02; Simulation

Doubly truncated (DT) data occur when event times are observed only if they fall within subject-specific, possibly random, intervals. In this article, we consider conditional maximum likelihood estimation for the regression parameters of the Cox-Aalen model with DT data. Based on gradient projection...